(1) Field of the Invention
This invention relates to a method for matching process trend. In particular, a method that involves matching the trend of process outcome with the trend of process variables to identify the variables that have an impact on the process outcome.
(2) Description of the Prior Art
In semiconductor manufacturing, the known method to identify a process variable that has an impact on the process outcome involves a numerical correlation study using least square method. This method is effective in identifying process variables that have a direct relationship with process outcome. It involves finding the “best fit” line in which the square of the distance between the points and this line is the minimum. Such means of finding “best fit” line takes into account all data points including the baseline shift which makes the best fitted line inaccurate.
However, most of the time, a variable and an outcome do not have a direct relationship. For such cases, the computed least square value will become insignificant as there may be characteristic shape of changes in the variable and outcome. To observe such characteristic shape of changes, process variables and outcome charts are plotted and reviewed manually to determine the probable process variables that have an impact on the process outcome. This manual mean of visual analysis which involves observation of baseline shift and changes of process trend pattern is tedious, subjective and prone to human error. In view of this, there is a need for an automated method for process trend matching to identify probable process variables that have impact on process outcome.
Prior art patent documents, U.S. Pat. No. 6,591,182 by Cece et al., U.S. Pat. No. 7,031,878 by Cuddihy et al., U.S. Pat. No. 5,951,611 by La Pierre, U.S. Pat. No. 6,577,323 by Jamieson et al., U.S. Pat. No. 5,339,257 by Layden et al., and U.S. 2003/0198388 by Wenzel et al. comprise features that relate to identifying probable process variables that have impact on process outcome. U.S. Pat. No. 7,031,878 by Cuddihy et al. relates to an automatic method for trend analysis wherein outliers are removed using standard statistical technique, performance data is split by time to allow linear or non-linear regressions to be run through each data segment, followed by evaluating the split points to determine the one most likely to represent a given problem.
Furthermore there are patents in the field of identifying variables that have an impact on a process outcome:
U.S. patent Publication (US 2006/0095237 to Wang et al.) proposes a system and method for yield management wherein a data set containing one or more prediction variable values and one or more response variable values is input into the system. The system can process the input data set to remove prediction variables with missing values and data sets with missing values based on a tiered splitting method to maximize usage of all valid data points. The processed data can then be used to generate a model that may be a decision tree. The system can accept user input to modify the generated model. Once the model is complete, one or more statistical analysis tools can be used to analyze the data and generate a list of the key yield factors for the particular data set.
U.S. patent Publication (US 2005/0130329 to Liao et al.) discloses a method for predicting a source of semiconductor part deviation. The method includes the steps of selecting at least one chart including part parameters and associating with each of the part parameters at least one fabrication process, which are stored in recipes, scanning the selected charts for deviations in the part parameters, wherein the deviations are determined by monitoring a trend of recent values of the part parameters, indicating the charts containing the part parameters wherein the part parameter values are determined as being outside of at least one trend tolerance value associated with the parameter, identifying, in each of the indicated charts at least one process associated with each of the part parameter deviations outside the at least one tread tolerance value, and determining a source of the parameter deviation by correlating each of the identified at least one processes. In one aspect of the invention, the selected chart includes the relationship between part parameters and processes.
U.S. patent Publication (US 2004/0088100 to Volponi) discloses a method of performing diagnostics on a system comprising receiving a plurality of measurement parameters, each corresponding to one of a plurality of parameters at a time k, forming a deviation vector from the plurality of measurement parameters, calculating an initial deviation vector from an initial fault vector, calculating a multiple fault isolation deviation vector using the initial deviation vector and the deviation vector, determining if an event is in progress using the multiple fault isolation deviation vector, performing statistical data validity to set a present inhibit flag and a past inhibit flag, and performing module performance analysis according to the present inhibit flag and the past inhibit flag.